Changes in human milk fatty acid composition and maternal lifestyle-related factors over a decade: a comparison between the two Ulm Birth Cohort Studies.
Linda P SizibaLeonie LorenzHermann BrennerPrudence CarrBernd StahlMarko MankTamás MarosvölgyiTamás DecsiÉva SzabóDietrich RothenbacherJon GenuneitPublished in: The British journal of nutrition (2020)
Human milk fatty acid composition varies during lactation and is influenced by maternal diet, maternal lifestyle-related factors and genetic background. This is one of the first studies to investigate a period effect, that is, the impact of lifestyle-related changes on human milk fatty acid composition, in two different cohorts. Lactating women were recruited from the general population a decade apart in Ulm, Germany, using similar methodology. Human milk samples collected 6 weeks postpartum were analysed (Ulm Birth Cohort Study (UBCS (2000)), n 567; Ulm SPATZ Health Study (SPATZ (2012)), n 458). Centred log ratio transformation was applied to fatty acid data. Principal component analysis was used to determine study-dependent fatty acid profiles. A general linear model was used to determine the study (or period) effect on fatty acid profiles adjusting for duration of gestation, age, education, delivery mode, smoking and pre-pregnancy BMI. Two principal components were retained (PC1 and PC2). PC1 was associated with UBCS, while PC2 was associated with SPATZ. PC1 comprised high SFA, and low MUFA, n-6 and n-3 long-chain PUFA (LCPUFA). The inverse was true for PC2. Although human milk remains a source of essential fatty acids, infants could be at risk of inadequate n-3 and n-6 LCPUFA intake through human milk. The differences in the human milk fatty acid profiles also reflect changes in maternal dietary habits in the more recent cohort, which may comprise lower intakes of dietary trans-fatty acids and SFA and higher intakes of vegetable oils.
Keyphrases
- human milk
- fatty acid
- low birth weight
- pregnancy outcomes
- preterm infants
- preterm birth
- gestational age
- birth weight
- physical activity
- cardiovascular disease
- metabolic syndrome
- healthcare
- public health
- adipose tissue
- type diabetes
- gene expression
- weight gain
- climate change
- machine learning
- deep learning
- social media
- risk assessment
- health information
- skeletal muscle
- insulin resistance